James C. Mathews

TL;DR: A technique to construct a simplification of a feature network which can be used for interactive data exploration, biological hypothesis generation, and the detection of communities or modules of cofunctional features, which implicate the PSGs in a potential immune tolerance mechanism of cancers.

TL;DR: The study suggests that utilization of mathematical tools for network-based analysis can provide novel insights into drug response and cancer biology, and adopts a discrete notion of Ricci curvature to measure the robustness of biological networks constructed with a pre-treatment gene expression dataset.

TL;DR: A novel network-based methodology is proposed that breaks the problem into smaller, more interpretable problems to improve the predictive power of anti-cancer drug responses in cell lines and finds that among the four drugs top-ranked with respect to prediction performance, three targeted the PI3K/mTOR signaling pathway.

TL;DR: In this article , the authors used standard stromal pathologist-assessed tumor infiltrating lymphocyte (TIL) quantification, quantitative multiplex immunofluorescence, and RNA-based gene pathway signatures to assess pretreatment TME characteristics associated pathologic complete response in patients with hormone receptor positive, HER2 positive early breast cancer treated in the neoadjuvant setting.